How to design incentive systems


Many believe that if you create the right system of incentives people will perform better at what they are needed to do.

For example, with sales people you just need to get the commissions and bonuses right and that will result in people meeting and exceeding targets.

But is this really the case?

An increasing amount of research (and a helping of common sense) suggests that it isn’t.

Linking a reward directly to behaviour has an unwelcome side effect – it tends to reduce how much you want to do it.

Ideally, you want behaviour to be intrinsically motivated: people do a good job because they want to, children eat greens because they want to, people turn off the lights when the leave a room because they want to.

In their book Intrinsic Motivation and Self-Determination in Human Behavior the authors, Edward Deci and Richard Ryan, write that “the research has consistently shown that any contingent payment system tends to undermine intrinsic motivation.”

Such payments can have a corrosive impact on organisational performance, especially when you are asking people to do complicated or interesting things.

People quickly learn just how much they need to do to get the payments, and no more.

Or they “game” the system – by making decisions that protect their own payments while ignoring the decisions that may provide a greater overall benefit.

It turns out that there are at least two things you can experiment with to break this cycle.

First, make rewards a surprise. If you can’t predict when you will be rewarded, you don’t link the reward to what you do, and that has less of an impact on your behaviour.

Second, it turns out that people are more motivated when given a choice between a bad task and a worse one.

Try this on your kids: see how much longer they do their homework when given an choice to do that, or clean the dishes versus being able to watch TV when they are done.

The silver bullet, however, is to aim for incentive systems that design in goal congruence.

Goal congruence simply means that individual goals are consistent with, or agree with the larger organisational goals.

It requires looking at more than just the person and their role but also consider how what they do interacts with and influences the larger organisational system.

This is easy to say, but not that easy to do.

But that is also why organisations that can pull this off should be able to show real improvements in organisational productivity and behaviour.

Are you as good as you think you are?


There appear to be no shortcuts to becoming competent at something.

All skills, rather inconveniently, seem to take time and effort to master.

Why is it then that some people believe that they are outstanding performers at an activity when it is clear to others that they are not based on their performance?

This appears to be because of a cognitive bias called the Dunning-Kruger effect, shown in the chart above.

When you are starting an activity, you may not be fully aware of what it means to be good at that activity.

As a result, you may be excessively confident of your ability and performance.

As you spend more time doing the activity and undergoing training, you become better at identifying what it means to be good.

As a result, your confidence in your ability to do the activity might also fall.

This can carry on until you reach a point where you can see that you are now doing better at the activity each time, and your confidence once again grows.

Once you are competent, perhaps even an expert, your confidence in being able to carry out the activity is now justified and is apparent to others through your results.

In essence, the way to avoid being trapped by the Dunning-Kruger effect is to become more self aware.

In her book Madness, Rack and Honey, the author Mary Ruefle writes about a remark made by the Vietnamese monk Thich Nhat Hanh on self awareness: “Before I began to practice, mountains were mountains and rivers were rivers. After I began to practice, mountains were no longer mountains and rivers were no longer rivers. Now, I have practiced for some time, and mountains are again mountains and rivers are again rivers.”

Or, as Confucius said succinctly: “Real knowledge is to know the extent of one’s ignorance.”

Why constraints are crucial to innovation


We are often told to “think outside the box”.

Working within constraints, however, may be crucial to actually being able to innovate and create something new and different.

When you are free of any constraints or limitations, it is difficult to see what will truly make a difference because you don’t really have anything to measure yourself against.

You might end up doing new things for the sake of newness, rather than because they are going to be a improvement on what has happened so far.

Take, for example, Frank Gehry’s design of the Walt Disney Concert Hall, hailed as one of the “most acoustically sophisticated concert halls in the world”.

According to the architect, the interior space was designed for stringent acoustic standards, and the limations and constraints that resulted from the standards drove the design and innovation choices that have made the hall a landmark.

A simple constraint can focus attention and create the conditions for generating innovative solutions.

Take the idea of Zero Emissions Cities. If you wanted to reduce emissions in a city to nothing, what would you do?

Governments and city officials would need to radically change their policies and incentives to support zero emissions energy initiatives.

You would need to think about how the energy infrastructure could be upgraded, the issues around smart mobility and logistics – moving passengers and freight around, and the way in which the environment and ecosystem would be managed.

The possibilities for innovation are endless – once you have imposed a constraint or target.

Coming closer to home, constraints can increase your own productivity.

One of the biggest time sinks for us is mobile phones. The endless screens mean that you could keep scrolling and reading for ever.

Software with features can result in you spending more time with the features and less time doing any useful work.

Most advice around personal productivity involves turning off phones and distractions and slimming down your work tools to the essentials needed to get on with the job.

According to Donald Sull of McKinsey, the key to improving the way in which you innovate is to pick simple rules to guide how you work.

Having these rules helps you prioritize, to assess where you are, to keep an eye on whether you are on target and can make a step change in improving your innovation processes.

You do need to think outside the box to come up with ideas and in order to be open to possibilities.

When it comes to action and innovation, however, the crucial next step may be to choose the right box to step into and work within.

Should knowledge be accessible to everyone?


Publically funded research in Europe could be free to access by 2020 if the European Union carry out necessary reforms.

At the moment, despite there being more information available than ever before, access to high quality research is still limited to people who can either pay for it or belong to universities that can afford the subscriptions.

This freezes out the vast majority of people from accessing scientific knowledge.

The Open Science movement is an attempt to change this, making the results of research and the underlying data more accessible to all levels of society.

The main arguments against open science are:

  1. The peer-review system operated by journals maintains quality.
  2. Scientists should be compensated for their work
  3. Widely available data could be misinterpreted by lay people.
  4. Making certain kinds of research findings public could mean they are misused, for example to create biological weapons.

The proponents of open science argue that:

  1. Publically funded research should be available to the public.
  2. Open access means that there will be more review by a more distributed readership.
  3. Open science will make findings more reproducible.
  4. More people can apply the findings

For individuals and businesses, the easiest thing to do right now is rely on the first few results of a google search to provide all the evidence they need to make a decision.

This results in inevitably narrowing the amount of information that is taken into account when analysing a situation and deciding what to do.

One of the benefits of a well written paper is that the author takes the effort to examine prior lines of thinking, point to seminal works in the field and set out why the information in the paper is new and relevant to you.

This contextual approach is crucial – relying on easily accessible information can create a bias and it is important to consider alternatives to the options that seem most obvious to make good decisions.

There appears to be little truly useful scientific information out there to help businesses improve how they operate, especially ones that operate in niche manufacturing fields.

Perhaps making scientific research more open and accessible is one way to change that and make organisations more productive and sustainable.

Some open science resources are:

How to invest in yourself


For a long time people were thought of as “resources”, lumped together in a generic mass of labour that had an economic purpose.

Many organisations still think of people in this way – and it’s in the title they give the department that deals with this task – Human Resources.

Is this the right term to describe this activity now?

The Economist has an interesting article on Gary Becker, the Nobel prize winning economist, who in the 1950s began to articulate a theory of economics based on “human capital” – investments in things that raise your own value.

Becker explains that a form of capital like a physical asset is something that yields income and other useful benefits over time.

Less tangible investments such as education, health or habits can also yield income and other useful benefits – and this is what economists refer to as human capital.

The most important ways to create human capital are through investing in education, training and health.

Human capital is something that an organisation cannot separate from you.

You can’t be forced to give up your knowledge, skills or health in the same way that your house, car or bank savings can be taken from you.

This creates a quandry for organisations such as banks or employers.

A bank may be happy to lend you money for a house, knowing that they can always get the house if you fail to make repayments, but they may be less happy to lend you money for an education.

Employers may be happy to invest in job-related training that makes you more productive on their equipment or technology but less willing to invest in generic education that makes you more marketable.

This is why many investments in human capital have to be funded by people themselves, rather than relying on others to fund it for them.

One form of investment is “opportunity cost”, the earnings forgone by someone who goes on to complete advanced education. Many others rely on savings for later education.

It is also important to value the total returns from human capital accurately.

One form of return is income – more money – which seems all important because it is so visible.

But you also have other useful benefits – more interesting work, more choice, perhaps more opportunities, that arise as a consequence of increasing your human capital.

You need to take into account all these potential returns as you decide where and when to invest in yourself.

Why we should all use email less


There’s a lizard inside your brain.

This is the part of your brain that tries to keep you alive, and it does this by being aware of what is happening around you.

Your brain has a strong “novelty” bias. If something new turns up, you stop and figure out what this new thing means for you – is it dangerous or not?

And, because it’s such an important (or used to be important in the days when sabre-tooth tigers were around) brain function to have, it can cut through everything else you are doing to get your attention.

In other words, you can be easily distracted by something new in your environment.

And the tools we use for work and life now are designed to distract us, and as individuals and organisations, we should think hard about whether that is something we should allow.

Daniel Levitin describes how multi-tasking is bad for you in his book The organized mind.

Take email, for example. You can’t predict when the next email will come into your inbox.

When it does, you get anything from a little icon in the bottom right corner of your screen to a big ding sound if your speakers are on.

It is simply impossible for your brain not to notice that something has changed in the environment in front of you.

Your brain responds chemically, burning up brain fuel (oxygenated glucose), increasing the stress hormone cortisol and gets your body ready to fight or flee.

When this happens hundreds of times a day, it make you much less productive. Just knowing that you have an unread email in your inbox drops your IQ by 10 points.

It turns out that multi-tasking is worse for you than smoking pot.

One reason why email (and facebook and every other social communication tool) is exploding is that the marginal costs of sending a message are so low.

It costs someone nothing to send a new message.

As a result, everyone sends more of them – something they wouldn’t do if they had a limit on the number they could send, or paid a price when they sent each one.

So what we do if we want to be more productive?

There are two things to try out.

First try and limit your exposure to novelty. If you need to work on something and concentrate, turn off email and your phone for a while.

It’s hard, but you’ll get more done more quickly without interruptions and your brain will be happier at the end of that time.

Second, work in time-blocks. This simply means having set times when you work and a set time when you check email and communicate.

This is what Paul Graham of YCombinator calls Maker’s Schedule, Manager’s Schedule.

In most organisations, a recurring complaint from workers is the volume of email that comes in every day.

If you are in a position of influence to make your organisation more productive, perhaps the best way is to make it OK for people to check email once or twice a day rather than having it on all the time.

How many legs does a sheep have if you call its tail a leg?



Because calling a tail a leg doesn’t make it one.

This riddle has been around for a few centuries and is often attributed to Lincoln, but actually goes back further.

It’s a useful thought to keep in mind, especially when you consider that governments often find it easier to redefine reality rather than do something about it.

At the same time, existing definitions may come under fire because they describe something as reality that people no longer think is the case.

An example is the definition of marriage.

You have a religious definition that is based on a relationship between a man and a woman.

And then you have a secular definition that is based on a relationship between two people.

Depending on how you have reached your own opinion on the matter, you may disagree with others as to which one should accurately represent reality.

In 2015, the government decided to redefine child poverty as based more around a lack of family morals rather than a lack of cash.

Campaigners for poverty reduction disagree.

In this TED talk by Rutger Bregman, he talks about how Margaret Thatcher called poverty a “personality defect”.

Bregman argues that if everyone had a basic income guarantee you would eradicate poverty and it would be much cheaper than all the programmes that try to remove it through education and helping the poor to help themselves.

The energy industry has suffered from this too.

In the period from 2006 – 2008, there was an effort by the government to redefine everything in terms of carbon rather than energy.

The focus became how to reduce carbon, rather than how to reduce energy.

When we look back at this period, it is possible that we will see that this has led to distortions in the market, and that change in definition has led to reducing efforts to invest in energy efficiency while increasing efforts to invest in green generation.

This means we use the same amount of energy – but use less carbon.

Not that making cleaner energy isn’t good for the planet.

It’s just that not using it at all in the first place is even better.

How to use data to understand and predict the future


The world’s largest corporations are increasingly investing in projects to try and use data for better decision making in their businesses, to improve how they work from marketing to operations.

Why is it then that nearly three-quarters of big data projects are unprofitable?

One explanation is put forward by Tricia Wang in this TED talk.

We use data to help us understand how the world around us works, and we hope that this understanding will help us predict what is going to happen in the future.

But, depending on how we approach the idea of data, this results in different tactics by different organisations.

The “hot” approach is the one of big data.

Everything is connected – the internet of things (IOT).

Data is collected automatically, recording everything from your browsing history to when your toaster turns on and off.

Tricia Wang has invented the term “thick data” for an approach to collecting data by observation – something done by the likes of ethnographers and anthropologists.

This is a modification of the term “thick description” that tries to explain behaviour and the context in which the behaviour takes place.

So, in big data, computers collect information from customer “touchpoints” – the places where you interact with the machines.

In thick data, people collect information by observing and interacting with other people.

Tricia’s example of how this results in different outcomes is the case study of Nokia.

The huge amount of data collected by Nokia from its customers and market research failed to alert them to the possibilities of the smartphone.

Tricia’s research showing that low-income Chinese people were willing to spend half their monthly income on buying a phone convinced her that the smartphone would take off.

And we all know what happened to Nokia when the iPhone took over the world.

In a big data world more is better – sample sizes are huge.

We collect millions of data points and store these in the cloud.

Tools like IBM’s Watson help you analyse and evaluate this data for not just quantitative insights but also, through natural language processing, for emotional components and behavioural predictions.

With thick data, we have a small number of data points.

Someone has to spend time with people, observing what they do, where they do it and draw conclusions on what that means for the future.

Big data helps you quantify the world.

All the measurements you take give you the ability to look at how people interact with your business in a level of detail beyond anything that was possible before and express this in numerical terms.

Thick data helps you explain why people do what they do.

Taking time to watch and interact with people gives you insights into the way they think and behave and, crucially, what they might do next.

The point is that it is not an either-or situation.

Using just big data is not enough.

Combining the power of big data to quantify and the power of thick data to explain can give you a better understanding of the situation.

Take a simple example of thick data in action.

If you have watched The Social Network, you’ll remember a scene where Zuckerberg is trying to figure out what to do with his system.

Over a drink, his friend comments that it would be great if people had a badge that said there whether someone was single or attached.

Zuckerberg has a flash of insight and adding that feature to facebook causes subscriptions to rocket.

In other words – if you work out how use both big data and thick data in your business, you are more likely to be able to better understand and predict the future.

How to create energy from underwater kites


In 2015, a £25m project was launched to install underwater “kite-turbines” in Holyhead Deep, off the coast of North Wales.

Swedish developer Minesto has built the turbines and plans to commission the project in stages, starting in 2017 with a 0.5 MW demonstration unit of their patented Deep Green ocean energy power plant.

Unlike airborne kites, which turn a generator on the ground, these underwater kite-turbines have a wing with a turbine attached directly to it.

The underwater current lifts the wing and the kite is steered in a figure-of-eight at several times the speed of the current.

The water flows over the turbine blades and turns them, producing electricity, which is then transmitted through to a cable to the kite-turbine’s tether on the seabed and from there to the grid onshore.

Most existing tidal technology is large, fixed and can operate only in currents that are faster than 2.5 meters per second.

Because the movement of Deep Green increases the speed at which currents flow over the turbine, it can operate at lower speeds than fixed installations, down to 1.2 meters per second.

Each turbine is rated at between 150 and 800 kW and can work submerged in depths of 15 meters to 300 meters.

Kite-turbines can also be up to 15 times lighter than fixed alternatives, at around 10 tonnes.

The locations for these generators have to be chosen so that they don’t interfere with shipping or other sea users.

Following the demonstrator project in 2017, the site will be gradually expanded to house 20 power plants producing 10 MW.

Minesto have also announced that they are looking to take the eventual size of the array to 80 MW.

The cost of energy from this technology could be around £1 million per installed MW at this point, although costs could decrease with scale.

The UK is in a unique position to harvest energy from tidal resource – it has around half the European tidal resource and 10-15% of global resource according to Minesto.

Tides are also very predictable, making this kind of technology very attractive if it can be deployed at scale because it uses renewable resource and its output can be predicted with a high degree of accuracy.

What the prices of batteries mean for storage applications


The prices of battery packs fell from close to $1,000 per kWh at the start of the decade to $227 in 2016, a drop of around 80% according to a McKinsey study released at the start of the year.

Current projections put them on course to fall below $200 per kWh by 2020 and below $100 per kWh by 2030.

What impact does the cost of batteries have on the overall business case for producing an electric vehicle?

Some interesting numbers are discussed in this Tesla forum article:

  • There are claims that Tesla’s internal cost of batteries ranges from $150 to $240 per kWh now.
  • GM revealed that their battery cost at cell level was around $145 per kWh.
  • A 60 kWh battery pack would make up $10,440 of the $37,495 Chevrolet Bolt at a pack price of $174.

This means that the cost of batteries for an electric vehicle drops to under a third of the price of a car and could drop to under a fifth by 2030.

Lithium-ion technologies dominate the battery storage market, making up 95% of new energy storage projects according to McKinsey research.

The same research found that battery storage applications are already economic in four important areas – demand charge management, grid scale power, small-scale renewables and storage and frequency response.

They also note that in applications such as demand charge management and small-scale renewables, lead-acid batteries may work better than lithium-ion.

It is likely that in the coming years packages of energy storage solutions for industrial and domestic use will become simpler and easier to buy and install.

Falling prices as the technology improves in any industry benefits consumers more than the producers – buyers will gain most of the benefit from price reductions in battery technology.

Energy storage has the potential to tranform the energy system as we know it, and it looks like it could happen faster than anyone expected.